- Systems (like software)
Devices – We should use devices to collect data. Sometimes people must collect data. But if we can use a tool it will save a lot of time and get rid of a ton of busy work. Let’s look at the airline and weather example. Instead of making people continuously report the temperature in various cities, devices collect this information. Could you imagine how much tickets would be if people had to report this data?
Systems (Like software) – Many times devices collect data and then people turn it into information for senior leaders to make decisions. Many employees in corporate America are “Deck Donkeys,” which means the solely create decks to share information. These Power Point decks are typical graphs, reports, etc. Taking the airline industry example, instead of someone constantly making reports on the weather and showing where there is inclement weather, the airline industry has software that automatically reports on severe weather. Based on the weather, systems can predict airport congestion, taxi times and even what runways will be available and when. You can read a blog o n how The Weather Company uses systems for prediction.
Humans – Humans ultimately make the decisions. Let’s look at the airline industry one last time. After looking over the information on freezing temperatures, the information is funneled to the pilots, control towers, and airlines so they can make the best decisions for passengers. More from The Weather Company:
Airlines cannot change the weather, but they can mitigate the effect if they know the impact in advance. By understanding situations and the potential of their impacts ahead of time, airlines can execute time-sensitive strategies (such as flight cancellation, flight swaps, reserve crew, and etc.) to mitigate such impacts.Could you imagine what would happen if ALL this work was completed by a human? There would certainly be errors and airline prices would be even higher! With the right devices collecting the data and the right systems transposing it into information, humans can focus on making strategic decisions that will make their customers happy. That is how technology should work for us.
Chapter Eight:SharePoint or Smartsheets. By the time a customer has called us, they have usually exhausted every resource within their business and often have hired a standard IT company that did not fix the root cause of their woes. Here are a few reasons why you might not have the data you want or need for your business. 1. You may not have the data. It’s not there at all in any of your databases or spreadsheets. For example, one of our customers wanted to know what projects everyone was working on. They did not understand why they could not see that level of detail. The reason, they didn’t have tools that were collecting that information. We integrated T-Sheets with SharePoint and now they have that data. 2. Your data might not be clean. Read, 4 Reasons Why Your Data is Not Clean. If you are using a spreadsheet to manage your business’s data, then you will most likely have errors in that data. It could be hard to trust it, too. 3. Data Integration problems. Sometimes the software we use is “closed.” This basically means that the software you are using cannot talk to other software. For example, SharePoint can integrate with virtually every type of software and share data in multiple ways. However, a spreadsheet, like Excel or SmartSheets, can’t talk to other software or share data effectively. 4. Data visualization problems. You might have the data you need, you just cannot see it. You may not have the tools you need to visualize the data… like Tableau and Power BI. See our data visualization story and an example of how this could happen in your business.
Chapter Twospreadsheets don’t manage big data sets well.) For example, a manager could get access to a Human Resource spreadsheet with employee names and other important information. Let’s say he has an employee named JoAnne, but she likes to be called Jo. He changes the data because he can and there are no restrictions preventing him. But there is a big problem. Now the source data – the system of record – is not accurate. (Check out our eBook on what it takes to have a System of Record.) JoAnne will be called different names in different versions of spreadsheets. Throw time in there, too. Perhaps “Jo” is a contractor and keeping her time with a spreadsheet and must give the time to the manager. The manager sends JoAnne’s hours and all contractors to Human Resources so they can get paid. The manager’s project data is being merged with human resource’s data. The problem is that we have two different names in the system. No V-lookup or Pivot Table is going to solve this. It’s going to take someone to manually go in and fix the data. This might not seem like a big deal, but as the company grows, these smaller errors will multiply in other departments. Once this happens, the employee data cannot be trusted, and it will take a lot of manual work to fix the errors each pay period. The data problems can become so big that businesses end up just not trusting their data, causing a lot of rework and manual data entry. The solution A lot of companies hope that the software an IT company is going to install will solve the data problem. Unfortunately, this just adds another layer of complexity to the original problem. The problem that needs to be solved is how are you going to clean up your data, and then collect that data and then show it in a way that lets you see the data in a new light. Ideally, you want to make decisions with information that automatically reports to you. Seeing year over year, and month to month views of data can quickly identify trends. But the first step is clean data.
How to Control Human Resource Employee Data[post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => how-to-control-human-resource-employee-data [to_ping] => [pinged] => [post_modified] => 2018-04-03 03:52:25 [post_modified_gmt] => 2018-04-03 08:52:25 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.hingepoint.com/?p=12991 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => WP_Post Object ( [ID] => 12971 [post_author] => 3 [post_date] => 2017-07-21 11:04:15 [post_date_gmt] => 2017-07-21 16:04:15 [post_content] => What is Data Mining? Data mining is looking at a lot of data and trying to get valuable information out of it. Data mining deals with large data sets that would take too long to go through manually. So, data scientists create and use programs or software to look at these huge data sets and discover patterns in the data. The core of data mining is turning data into information. It can be overwhelming to look at a lot of data and not see the value in it. But what happens if you are a company and do not have so much information you need a program to determine the data you have? When dealing with smaller sets of data, you don’t necessarily need to hire a team of data scientists. You need someone who understands data and can extract it enough to show you it visually. HingePoint Data and Data Detective Work Before you can mine your data for trends, you need to understand what data you have and if it is good or bad data. This is fundamental to using data to maximize your business. We call this the Data Detective phase of our unique process. The goal is to get Hinge Point Data, which is data that if accessed and visualized the right way can revolutionize and transform your business. A HingePoint is the point where something literally pivots. It’s the turning point where you are going to see a significant change take place. We found this happens best when you have the right data to make the best decisions or keep employees and customers the best informed. HingePoint executes this fundamental level of data detection with our data dictionary work. When we work with a customer, we go into the data and define every piece of data they have. With our Data Dictionary we identify the following:
- Where is it?
- What database?
- What table?
- What system?
Chapter Four:data is clean and can be trusted. If you don’t have data you can trust, then you definitely cannot use this data to make sound business decisions. Currently, a lot of companies look at their sales and financial data as line items on a sheet. If you are not looking at accurate data in a visual manner you’re probably missing a trend or an extra expense about your business. Here’s an example: One of our customers had a financial system made out of PDFs. They had about six restaurants they were tracking. They would collect the finances for each of the restaurants and make separate PDFs. The PDFs would be shipped to the CFO team and they would dissect the information. Usually, the information was more than a month late because it took a while to build the reports. We built a financial dashboard. This collects all the information from the PDFs and puts the information on one screen. You can instantly get simple, comprehensive views of critical financial information on your phone. The customer had the ability to select what they wanted to compare from each restaurant in pie charts. So for example, if they wanted to see how much money each restaurant was spending on entertainment, they could easily see it. As soon as the financial dashboard came online… the customer realized they were spending way too much money on music and entertainment in one of their venues. They were able to make the decision to stop hiring so many bands immediately. Before the data wasn’t accessible. It wasn’t visible. The entertainment data was a line item in six separate PDFs. It also wasn’t in the same place. We created a dashboard to show side by side views of expenses like music and entertainment. They could see as a percentage of the pie that it was huge. As soon as they were able to visually see the data they could tell where their money was going and what changes needed to be made.
Often when we launch or upgrade new software like SharePoint for our customers, what they are really after is clean data.
We want to keep track of important information that will make us smarter about our business. When we work with a new customer that wants to fix their SharePoint or Salesforce, we inevitably find that their data is not clean.
To get systems to work the way the customer wants them to, we must help clean this data up so their software will be able to do what they want it to do, which usually is show accurate data.
We often get the question, why isn’t my data clean in the first place?
There are factors that can contribute to data that is not clean.
1. Usually, the data architecture is wrong. In other words, the way the databases were set up and the way different kinds of data related to each other are wrong. In a database, there are different tables that relate to each other. And that is the subject of data architecture… what columns are on which tables and how they relate to each other? So if you don’t set it the tables and databases up correctly, then while drilling down on your data you will get problems in terms of categorization or classification.
Bottom line, tables, and databases need to be set up properly. If you do not know how to do this, you need to find a consultant or hire someone who understands how to set this up. It’s critical if you want to use data to maximize your business.
2. Permission Issues – Sometimes employees who should not are changing data. Someone had permissions that they were not supposed to have.
Make sure that only the people that need to have permission to edit data have the right settings to do so. Set appropriate security permissions for employees. For example, only accountants should have permission to edit accounting data. If you are using something like Excel to manage financial data, then it might be time for a better system.
3. Data Entry Problems– Redundant data entry is a major culprit to unclean data. If you need to enter data multiple times, then this multiplies potential human errors. Errors also occur when copying it from one place to another.
To prevent this, make sure data is automated as much as possible. Eliminate as much manual entry as you can. Let software and systems do that data transfer rather than people. Software can talk other software. Integration part.
4. Data Entered Wrong – The alternative is that the data was entered incorrectly the first time. Ideally, customers can use a system that guides people through the data entry process. You can use checkboxes and dropdowns with limited possible entries as guides to control what data goes where. Many software systems have controls on what you can enter.To prevent this, make sure data is automated as much as possible. Eliminate as much manual entry as you can. Let software and systems transfer data rather than people. Software can talk to other software.